27 Selly Arteti Zega
The First International Conference on Engineering, Technology and Applied Business 2014
Batam-Indonesia, 4th December 2014
Paper-JT- 062: Predicting Animated Film of Box-Office Success with Neural Networks
Riwinotoa*, Selly Artaty Zegaa, Gia Irlandaa
a
Multimedia and Networking, Department of Informatics, Politeknik Negeri Batam, Parkway Street Batam Center, Batam,
Kepulauan Riau 29461, Indonesia
*Corresponding author: [email protected]
ABSTRACT
Animation industry involves huge funds in production process and its success will also give a great income.
Predicting animated film of box-office has intrigued many scholars and industry leaders as a challenging problem.
The success of animated films is obtained by objective parameters: the actors/actress, animation studio, genre,
MPAA rating and the sequel of the film using neural network. In this study, the use of neural networks in predicting
the financial performance of 120 animated films from 1995 until 2013 is explored. There are three categories of
financial performance that become the class label of this study, they are: low, medium and high. Our prediction
result in correctly classified instance is 66.67%, with the value of epoch: 0, number of epoch: 500, learning rate: 0.3
and momentum: 0.2. It is expected that this prediction can help animation film industry to predict the expected
revenue range before its theatrical release.
Keywords: animated film, financial, predict, neural network and box office
Politeknik Negeri Batam, ICC Universiti Teknologi Malaysia, Asian Fellowship of Academic Professionals (AFAP)
Batam-Indonesia, 4th December 2014
Paper-JT- 062: Predicting Animated Film of Box-Office Success with Neural Networks
Riwinotoa*, Selly Artaty Zegaa, Gia Irlandaa
a
Multimedia and Networking, Department of Informatics, Politeknik Negeri Batam, Parkway Street Batam Center, Batam,
Kepulauan Riau 29461, Indonesia
*Corresponding author: [email protected]
ABSTRACT
Animation industry involves huge funds in production process and its success will also give a great income.
Predicting animated film of box-office has intrigued many scholars and industry leaders as a challenging problem.
The success of animated films is obtained by objective parameters: the actors/actress, animation studio, genre,
MPAA rating and the sequel of the film using neural network. In this study, the use of neural networks in predicting
the financial performance of 120 animated films from 1995 until 2013 is explored. There are three categories of
financial performance that become the class label of this study, they are: low, medium and high. Our prediction
result in correctly classified instance is 66.67%, with the value of epoch: 0, number of epoch: 500, learning rate: 0.3
and momentum: 0.2. It is expected that this prediction can help animation film industry to predict the expected
revenue range before its theatrical release.
Keywords: animated film, financial, predict, neural network and box office
Politeknik Negeri Batam, ICC Universiti Teknologi Malaysia, Asian Fellowship of Academic Professionals (AFAP)